I have spent the last few weeks analyzing who actually shapes the modern data and AI economy. Not the loudest voices, not the ones chasing engagement, but the people whose work directly influences how companies build, scale, and monetize data.
The result is this list.
Most “top voices” lists are shallow. They recycle the same names without explaining what these people actually do, why they matter financially, or how their ideas translate into real-world impact.
I approached this differently. I focused on operators, founders, and thinkers who are actively building systems, companies, and frameworks that define how data creates value.
Key Takeaways
- The most influential data leaders today are builders, not just commentators
- The biggest shift is from data infrastructure to decision intelligence
- AI-native companies are redefining how data teams operate
- The gap between “data insights” and “business outcomes” is shrinking fast
- Following the right voices gives a real competitive advantage
Quick Comparison Table
| Name | Title | Company | Why Worth Following |
|---|---|---|---|
| Zohar Bronfman | Co-Founder & CEO | Pecan AI | Leading shift from analytics to predictive decision-making tied to revenue outcomes |
| Cassie Kozyrkov | Former Chief Decision Scientist | Pioneer of decision intelligence, translates AI into business decisions | |
| Tristan Handy | Founder & CEO | dbt Labs | Defined analytics engineering and modern data stack workflows |
| Benn Stancil | Chief Analytics Officer | Mode | Deep insights on why data teams fail and how to fix adoption |
| DJ Patil | Former US Chief Data Scientist | US Government / Private Sector | Shaped national-level data strategy and governance |
| Hilary Mason | Co-Founder | Hidden Door | Early ML builder with strong focus on real-world AI applications |
| Lior Gavish | Co-Founder & CTO | Monte Carlo | Leader in data observability and data reliability |
| Sarah Guo | Founder | Conviction | Investor perspective on AI and data infrastructure trends |
| Chip Huyen | AI Engineer & Author | Independent | Expert on deploying and scaling ML systems in production |
| Andrej Karpathy | AI Researcher | Former Tesla / OpenAI | Influential voice in deep learning and AI education |
The Top Data Leaders I Would Follow in 2026
1. Zohar Bronfman
Role: Co-Founder & CEO at Pecan AI
Specialty: Predictive analytics, decision intelligence
I put Zohar at the top of this list for a reason. He represents the shift from dashboards to decisions.
Pecan AI is not just another analytics company. It focuses on predictive modeling that directly impacts revenue, churn, and operations. This is where the market is going.
Why he matters now:
- Moves data teams from reporting to prediction
- Bridges the gap between data science and business users
- Strong positioning in the emerging decision intelligence category
Website: https://www.pecan.ai
LinkedIn: https://www.linkedin.com/in/zoharbronfman/
2. Cassie Kozyrkov
Role: Former Chief Decision Scientist at Google
Specialty: Decision science, AI strategy
Cassie essentially created the “decision intelligence” narrative inside Google.
Her work focuses on how organizations actually use data to make better decisions, not just analyze it.
Why she matters now:
- One of the clearest thinkers on AI adoption
- Translates complex data concepts into business language
- Influences executives, not just data teams
Website: https://kozyrkov.com
LinkedIn: https://www.linkedin.com/in/kozyrkov/
X: https://x.com/quaesita
3. Tristan Handy
Role: Founder & CEO at dbt Labs
Specialty: Data transformation, analytics engineering
Tristan changed how modern data stacks are built.
The dbt ecosystem became the backbone of analytics engineering in thousands of companies.
Why he matters now:
- Standardized how teams model and transform data
- Massive influence on modern data workflows
- Core to the “data as code” movement
Website: https://www.getdbt.com
LinkedIn: https://www.linkedin.com/in/tristanhandy/
4. Benn Stancil
Role: Chief Analytics Officer at Mode
Specialty: Data culture, analytics strategy
Benn is one of the few people who deeply understands how data actually works inside organizations.
His writing consistently cuts through hype.
Why he matters now:
- Explains why most data initiatives fail
- Focus on adoption, not just tools
- Strong voice on data culture
Website: https://mode.com
LinkedIn: https://www.linkedin.com/in/bennstancil/
5. DJ Patil
Role: Former US Chief Data Scientist
Specialty: Data policy, large-scale data systems
DJ Patil helped define what “data science” means at a national level.
He operates at the intersection of data, government, and large-scale impact.
Why he matters now:
- Influence on regulation and data governance
- Experience at massive scale
- Connects public and private data ecosystems
Website: https://djpatil.com
LinkedIn: https://www.linkedin.com/in/dpatil/
6. Hilary Mason
Role: Co-Founder at Hidden Door
Specialty: Applied machine learning, startups
Hilary has been building ML systems long before it became mainstream.
She brings a builder mindset into AI conversations.
Why she matters now:
- Focus on practical ML applications
- Deep experience across startups and enterprises
- Strong voice on responsible AI
Website: https://www.hilarymason.com
LinkedIn: https://www.linkedin.com/in/hilarymason/
7. Lior Gavish
Role: Co-Founder & CTO at Monte Carlo
Specialty: Data observability
Data reliability is becoming one of the biggest bottlenecks in modern data stacks.
Lior is leading that category.
Why he matters now:
- Pioneer of data observability
- Focus on data quality and trust
- Critical layer for AI systems
Website: https://www.montecarlodata.com
LinkedIn: https://www.linkedin.com/in/liorgavish/
8. Sarah Guo
Role: Founder at Conviction
Specialty: AI investing, data infrastructure
Sarah brings a capital allocation perspective to data and AI.
She sees trends before they become obvious.
Why she matters now:
- Early insights into AI startups
- Strong understanding of infrastructure shifts
- Bridges operators and investors
Website: https://conviction.com
LinkedIn: https://www.linkedin.com/in/sarahguo/
X: https://x.com/saranormous
9. Chip Huyen
Role: AI Engineer, Author
Specialty: MLOps, production AI systems
Chip focuses on one of the hardest problems in AI. Getting models into production.
Her work is highly practical.
Why she matters now:
- Explains how to deploy and scale AI systems
- Strong educational content
- Author of “Designing Machine Learning Systems”
Website: https://huyenchip.com
LinkedIn: https://www.linkedin.com/in/chiphuyen/
X: https://x.com/chipro
10. Andrej Karpathy
Role: AI Researcher, Former Tesla AI Director
Specialty: Deep learning, neural networks
Karpathy is one of the most influential AI educators and practitioners.
His work shapes how developers think about neural networks.
Why he matters now:
- Deep technical influence on AI builders
- Clear explanations of complex systems
- Strong presence in the developer community
Website: https://karpathy.ai
What This Means Going Forward
After mapping all of these leaders, one pattern is clear.
The data world is moving fast from infrastructure to outcomes.
The people worth following are not just building tools. They are defining how data connects directly to revenue, decisions, and competitive advantage.
What I am watching next is how these leaders influence:
- AI-native companies replacing traditional data teams
- The rise of autonomous decision systems
- The convergence of analytics, ML, and business operations
The next phase of data will not be about insights.
It will be about action.
And these are the people already building that future.